Human analysts are often tasked with analyzing data with little or no prior knowledge about the data. Large amounts and/or varying formats of data can make such an analysis time consuming, costly, error-prone, or even unfeasible.
Current software systems can be used to assist with parsing, characterizing, and extracting the data. However, such systems may require large amounts of manual setup, may provide limited characterization, may not adjust well to changes in data format, and may still miss or misinterpret relevant data.
Therefore, data characterization systems can be improved by methods and systems that can automatically and dynamically characterize data.